Facial expression recognition using human machine interaction and multi-modal visualization analysis for healthcare applications

作者：

Highlights：

• MMVA is introduced for improving less-complex processing of HMI in health monitoring.

• It is designed to identify facial expressions of a patient using input visualization.

• It relies on 3 layers of CNN for texture classification, correlation & detection.

• The proposed method achieves 95.702% of recognition accuracy.

摘要

•MMVA is introduced for improving less-complex processing of HMI in health monitoring.•It is designed to identify facial expressions of a patient using input visualization.•It relies on 3 layers of CNN for texture classification, correlation & detection.•The proposed method achieves 95.702% of recognition accuracy.

论文关键词：CNN,Computer vision,Face visualization,Healthcare systems,Human-machine interaction

论文评审过程：Received 7 August 2020, Revised 19 September 2020, Accepted 2 October 2020, Available online 7 October 2020, Version of Record 17 October 2020.

论文官网地址：https://doi.org/10.1016/j.imavis.2020.104044